Process and architecture of robotic system to mimic animal behavior in the natural environment

ABSTRACT

A robotic architecture for capturing the autonomous performance advantages the animal models enjoy in the natural environment is disclosed. A biomimesis process is employed to allow selective utilization of basic physical components and adaptation of a common control paradigm for each of different vehicle types. The biomimetic architecture involves five functional elements: a basic biomorphic plant for capturing the biomechanical advantages of the model organism; a neural circuit-based controller consisting of a finite state machine; myomorphic actuators producing linear graded force in response to trains of current pulses for mediating movements; labeled line code output by neuromorphic sensors; and a reactive behavioral sequencer executing command sequences defined within a behavioral library.

CROSS REFERENCE TO RELATED APPLICATIONS

The present application is a continuation application of U.S.application Ser. No. 10/898,673, filed Jul. 23, 2004 and entitled“PROCESS AND ARCHITECTURE OF ROBOTIC SYSTEM TO MIMIC ANIMAL BEHAVIOR INTHE NATURAL ENVIRONMENT”, which claims priority of U.S. ProvisionalPatent Application No. 60/489,645, filed Jul. 24, 2003 and entitled“PROCESS AND ARCHITECTURE OF ROBOTIC SYSTEM TO MIMIC ANIMAL BEHAVIOR INTHE NATURAL ENVIRONMENT both of which are incorporated herein byreference in their entirety.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Part of the work leading to this invention was carried out with UnitedStates Government support provided by:

Defense Advanced Research Projects Agency (DARPA) and Defense SciencesOffice (DSO) through Office of Naval Research (ONR) Grant No.N00014-98-1-0381;

DARPA through ONR Grant No. N00014-02-1-0428; and

ONR Grant No. N00014-04-1-0286.

Therefore, the U.S. Government has certain rights in this invention.

BACKGROUND OF THE INVENTION

Previous attempts to develop biomimetic robots required actuation andsensing to be performed by conventional technologies (e.g. motors,strain gauges, etc.). In particular, robots operating with conventionaltechnologies require extensive analog-to-digital (A/D) anddigital-to-analog (D/A) interfaces between the processor, sensors andactuators. These models have failed to employ neuronal codes derivedfrom an analysis of the activity of neuronal circuits of the modelanimal. Thus, while certain anatomical likenesses have been employed inprior approaches, the control methodologies employed have not beenpremised upon the innate behavior of the animal in nature.

BRIEF SUMMARY OF THE INVENTION

The presently disclosed invention is a robotic architectureinstantiated, for purposes of illustration, as two different robots,each capturing the autonomous performance advantages that the animalmodels enjoy in the natural environment. The two robots are: 1) alobster-based ambulatory robot; and 2) a lamprey-based undulatory robot.Each robotic system comprises an operational architecture that relies onreverse engineering of model animal systems and a basic physicalarchitecture which can be modified to implement a variety of biomimeticrobots that combine ambulatory, undulatory or other types of propulsion,depending upon the respective model animal.

To build robots based on animal models, a biomimesis process isemployed. This process allows the selective utilization of physicalcomponents and adaptation of a basic control paradigm for each ofdifferent vehicle types. The biomimetic architecture involves fivedifferent functional elements.

First, a basic biomorphic plant for each robot captures thebiomechanical advantages of the model organism by using the general bodyform and appendage set of that organism.

Second, the brain of the robot is a neural circuit-based controller thatconsists of a finite state machine. The state machine incorporates acommand neuron, a coordinating neuron and a central pattern generatormodel that controls actuators throughout the biomorphic plant.

Third, the system utilizes myomorphic actuators. These actuators areartificial muscle-based linear actuators that produce linear gradedforce in response to trains of current pulses for mediating themovements of the robot.

Fourth, the processes that trigger or modulate behavior as a result ofenvironmental inputs, referred to herein as “releasers,” are embodied inlabeled line code which is output by neuromorphic sensors. The robotsensors code environmental information in the same fashion as thesensors of the model organism and readily interface to the neuralcircuit-based controller. The labeled line coding quantizes the timing,amplitude, and orientation of the input stimulus. As in the modelorganism, the sensory modalities are orientated relative to gravity,direction and contact.

Finally, to achieve reactive autonomous behavior, a reactive behavioralsequencer executes sequences of commands defined within a behaviorallibrary. The contents of the library, indexed by releasers, are based onreverse-engineered behavior of the animal model. These commands controlthe robot subsystems by modulating the internal state variables thatspecify ongoing behavior. The queue-based behavioral sequencerreactively selects behavioral sequences in response to sensor-mediatedreleasers. As will be discussed, the behavioral sequencer not onlyqueues commands according to the relevant releasers, but also has thecapability of adapting already-enqueued commands on the basis ofsubsequently identified commands.

The robotic system is based on reverse-engineered animal model systemsthat operate with impunity in the candidate operational environment ofthe robot. Due to the underlying neuronal network architecture, thecontrollers are extensible to the entire behavioral repertoire of theanimal model.

The robot system is autonomous. A robot system can perform missionsunder supervised autonomy; for instance, it can, in conjunction with alane marking system, function as an organic mine hunting system foroperation in cluttered littoral environments.

In another aspect of the presently disclosed invention, an improvedmethod for forming an artificial muscle from a shaped memory alloy (SMA)material is disclosed. Using an appropriate band of crimping material, aloop of SMA is formed at one end which enables simple mechanicalconnection to a lightweight, high strength fiber serving as anartificial ligament for interfacing the SMA muscle to a mechanicalsupport. An electrically-conductive interface to a voltage supply isalso provided for selectively heating the SMA material, wherebycontraction occurs.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

The invention will be more fully understood by reference to thefollowing detailed description of the invention in conjunction with thedrawings, of which:

FIG. 1 is a plan view of an ambulatory lobster-based biomimetic robotdeveloped according to the principles of presently disclosed invention;

FIGS. 2A and 2B are side elevation views of the robot of FIG. 1;

FIGS. 3A and 3B are front and rear elevation views of the robot of FIG.1;

FIGS. 4A, 4B, and 4C are detailed views of a leg appendage of the robotof FIG. 1;

FIG. 5 is a plan view of an undulatory lamprey-based robot developedaccording to the principles of the presently disclosed invention;

FIG. 6 is a detailed view of a hull portion of the robot of FIG. 5;

FIGS. 7A and 7B are top and side views of an undulation module of therobot of FIG. 5;

FIGS. 7C and 7D are top and side views of a pitch/undulation module ofthe robot of FIG. 5;

FIG. 8 is a top view of a portion of an undulatory actuator system ofthe robot of FIG. 5;

FIG. 9 is a detailed view of an actuator system as used in the robots ofFIGS. 1 and 5;

FIG. 10 is a schematic view of the actuator system of FIG. 9;

FIG. 11 is an organizational depiction of the controller architectureemployed in the robot of FIG. 1;

FIG. 12 illustrates a linked list command stack as employed in therobots of FIGS. 1 and 5;

FIG. 13 is a flow chart illustrating an event loop performed by acontroller of the robots of FIGS. 1 and 5;

FIG. 14 illustrates the functional organization of a leg state machinefor the robot of FIG. 1;

FIG. 15 illustrates the X-Y deflection of a leg tip of the robot of FIG.1 with different temporal sub-command combinations;

FIGS. 16A and 16B illustrates exteroceptive reflexes mediating rheotaxicresponse to asymmetric flow and surge, respectively, in the robot ofFIG. 1;

FIG. 17 illustrates the control loop implementing reactive behavioralautonomy in the robot of FIG. 1;

FIG. 18 illustrates autonomous vectored locomotion in the robot of FIG.1;

FIG. 19 is a detailed view of one portion of the actuator system of FIG.10;

FIG. 20 illustrates a byte mask for antennal sensors for the robot ofFIG. 1;

FIG. 21 illustrates an exemplary display screen for a software toolenabling the development of robot behavioral sequences premised uponanimal behavior according to the principles of the presently disclosedinvention;

FIG. 22 depicts a table of behavioral sequences compiled using thesoftware tool of FIG. 21;

FIG. 23 is a flowchart depicting an initialization sequence performed bythe controller of the robot of FIG. 1;

FIG. 24 is a flow chart illustrating a range of possible commandsequences which can be commanded within the robot of FIG. 1;

FIG. 25 illustrates a command sequence for implementing a behavioralresponse to a sensor-detected condition in the robot of FIG. 1; and

FIG. 26 illustrates a command sequence for enabling the robot of FIG. 1to respond to externally received commands.

DETAILED DESCRIPTION OF THE INVENTION

A biologically-based robotic architecture consists of five principalcomponents, each to be described in detail below. These components are:a biomorphic plant; a neural circuit-based controller; myomorphicactuators; neuromorphic sensors; and a reactive behavioral sequencer.

(1) Biomorphic Plant

The biomorphic plant, or biomimetic or physical plant, is the vehiclestructure which is based on an animal model adapted to a particularniche. The vehicle plants are typically composed of a hull, powersupply, locomotory effectors, control surfaces and appendages, andadaptive sensors, which are generalized, and in many cases conservedamong animal groups. The plant differs for underwater versus terrestrialapplications with regard to the need for hydrodynamic control surfacesand a watertight electronics bay. In addition, the impact of buoyancyprovides different requirements of actuator force necessary to mediatesupport against gravity versus translational propulsion. Due to theirconservative organization, component modules are assembled in differentcombinations to mimic different animal models. For example, analligator-based robot combines both undulatory and ambulatory effectors.

The embodiments of the robotic systems described herein are specificexamples of how the general techniques, processes, materials, etc., arepracticed to devise biomimetic robotic systems. A wide variety of robotsmay be realized according to the general structure and conceptsdescribed above and utilizing variations on the specific implementationsdescribed below.

a. Lobster-Based Ambulatory Robot

With respect to FIGS. 1 through 3B, the lobster vehicle 10 developedaccording to the presently disclosed biomimetic approach use walkinglegs 12 having three degrees of freedom to mediate locomotion. The legsare attached to an electronics bay or hull 14. An external or internalbattery pack 16 is also provided in one embodiment, whereas in anothertethered embodiment, power is received via watertight tether (notillustrated). The electronics bay is a water tight box with a machinedlid and o-ring seal to facilitate access to the electronics components.The lid of the hull features a light-emitting diode (LED) 18 that can beused to indicate the status of the vehicle, such as water in hull,received sonar command, etc., for external inspection. An externalflange 20 allows the leg assemblies to be mounted on the hullindependently. Each leg has a water-tight electrical feed-through thatallows leg assemblies to be changed out rapidly.

Two generations of lobster-based ambulatory robots have been developedfor operations in, for instance, the littoral zone of the ocean,harbors, estuaries, and rivers. One embodiment of the ambulatory robotsuses external power and may be tele-operated via a float and RF modemcommunications link. The other has onboard power 16, an embeddedcontroller 22 and is capable of supervised autonomous operation via asonar interface.

The watertight hull contains a motherboard, leg current driver boards, amotor controller board, a sonar board, and current drivers for the trimappendages. The motherboard houses power management circuitry, thecompass 24, and pitch and roll inclinometers 26, 28.

With respect to FIGS. 4A through 4C, eight modular walking legassemblies 30 are attached to a flange 20 on the hull 14 in thelobster-based ambulatory embodiment. Each leg assembly is composed ofvertical posts 32 that contain muscle modules 34A, 34B that protract andretract the leg around a capstan 36 that supports the more distaljoints. Two other segments 40, 42 house paired antagonistic actuatorsthat cause elevation/depression and extension/flexion. As shown in FIG.9, a leg segment preferably comprises a myomorphic muscle beginning andending at one point and looped around another point. In FIG. 9, thesepoints are cylindrical. In FIG. 4A, the termination point is provided asa plate to which the muscle is attached and the other point is a pulley.Further still, the muscle may be fixed to the beginning and ending pointvia KEVLAR (E. I. du Pont de Nemours Company, Incorporated) ligamentsfurther described in the context of FIG. 19. Leg segments house springs46 that prevent overstress of artificial muscle actuators and providesome measure of compliance.

A separate battery compartment 16 that fits in a sliding flange containsthe battery packs. During development, the system has been powered bynickel metal-hydride rechargeable batteries, though mission length canbe increased substantially by use of lithium ion-polymer batteries. Oneskilled in the art will realize that a variety of battery technologiescan be adapted for use in the disclosed biomimetic robot architecture.

Anterior 50 and posterior 52 hydrodynamic control surfaces analogous tothe claws and abdomen of the lobster are controlled in pitch by DCmotors 54, 56 operating through jackscrew assemblies. Separate nitinolshaped memory alloy (SMA) actuators (not illustrated) control the yaw ofthe anterior surfaces and pitch of the tail fan 58. A pair of antennae60A, 60B can be positioned at one of four yaw orientations or can beswept between any of the four positions by a separate DC motor/geararrangement 62. The antennae each have cooperating gears such thatrotation of one antenna in one rotational direction results in acomplimentary rotation of the other antenna in the opposite rotationaldirection.

The external battery bay 16 is mounted on the lower surface of the hull14 with a sliding flange allowing the battery to be changed out withoutopening the electronics bay pressure vessel. One of the major sources ofvariability in the performance of the vehicle during testing was thefact that when large numbers of nitinol actuators were activated inparallel, the effective load of the actuators became lower than that ofthe conductor connecting the batteries to the power FETs. To addressthis problem, the battery bay was configured to have four separate powercircuits, one for each of the leg power boards (discussed subsequently).Thus, in one embodiment, the power supply consists of twenty-nickelmetal hydride batteries arranged in four parallel sets of five batteriesin series. This arrangement provides a separate 6.5V power supply foreach of the four leg driver boards and minimizes the current in any onecircuit. The total load of the motherboard is relatively low and isaccommodated by one of the four battery circuits. The battery pack isconnected to the electronics bay by an external cable (not illustrated)with four parallel sets of conductors. Two watertight connectors allowthe battery pack to be changed out rapidly. Tests indicate that thenickel metal hydride batteries used in the disclosed lobster-basedambulatory robot have a life of about 50 minutes to 1.5 hours, dependingon operations.

There are separate hull feed-throughs for the wires to the drive motorsfor the claw and tail pitch control motors on the front and rearsurfaces of the hull (not illustrated). A third hull feed-through allowsthe serial bus to be connected to an external laptop to allowreprogramming and/or external operation for debugging purposes. The lidof the pressure vessel houses a sonar transducer 64 and the antennadrive motor 62. Two additional feed-throughs pass the sonar leads, themotor controls, and the returned signals from the antenna strain gaugesthrough the lid.

Within the hull are a number of internal interface circuit boards: amotherboard; an actuator control or leg driver boards; a controllerboard; and a motor-driver board.

One embodiment of the lobster-based ambulatory robot 10 uses a board setbased on surface mount technology. The interface boards are plugged intoa motherboard that contains the serial bus, the pitch and rollinclinometers 26, 28 and the compass 24. The motherboard also houses amoisture sensor that reports leaks through an LED 18 mounted on theelectronics bay lid. The motherboard also has circuitry to interface toa thermistor (not illustrated) to allow modulation of the pulse widthduty cycle lookup tables (LUTs) relative to the temperature of theexternal seawater. The motherboard has slots for seven interface boards.

The leg driver or actuator control boards house the power controlcircuitry to drive one pair of leg modules 30. These boards implementthe recruiter that allows the graded actuation of nitinol musclecontractions. These boards are the high current pathway between thebatteries and the nitinol artificial muscle actuators. In oneembodiment, the on-board circuitry consists of a serial bus thatconnects the board to the controller, a peripheral interface controller(PIC) microcontroller that generates the pulse trains that energize thenitinol actuators, power FETs, and a separate power bus from thebatteries.

On each actuator control board, there are six external jacks thatconnect the board to the respective leg modules 30. Each jack containsthe control wires to two actuators that operate each of the three legjoints 36, 40, 42. The leg driver board receives vectored serialcommands to turn on or turn off a current pulse train to one actuatorelement. As shown in FIG. 9, the pulse trains can have one of threepulse width duty cycles levels specified as low, medium, and high (L, M,H) depending upon the control signal. The actual duty cycle associatedwith each level can be adaptively assigned by the controller to modulatethe intensity of leg movements associated with each duty cycle level.

As will be appreciated by one skilled in the art, the specificimplementation of the actuator control boards may be varied as long asthe fundamental goal, instantiating electronic neurons through a pulsewidth duty cycle varying-circuit responsive to byte commands from acontroller, is realized.

The brain of the robot is housed in a separate controller board thatsupports a Persistor Instruments Inc. microcontroller 22. Themicrocontroller is a 3-volt Motorola, Inc. 68020 microprocessor with acompact flash memory module. The board connects the microcontrollerserial ports to the serial bus of the motherboard. The board also housesa voltage regulator to reduce the 6.5V power coming from the motherboardto the processor Vcc. The Motorola processor is supported in theMetrowerks CodeWarrior programming environment (both PC and MACcompatible) through a cross-compiler library and is programmed in the Cprogramming language. The code can be downloaded from the laptop throughthe serial bus or transferred directly to the compact flash memorymodule using a PCMCIA adapter in a laptop computer, for example.

The motor driver board performs several functions. First, it hascontrollers for the drive motors for the claw pitch 54, the tail pitch56 and the antenna yaw 62. Secondly, it provides an interface to theantennal strain gauge sensors (not illustrated) and quantizes the sensoroutput into a labeled line code. Third, the board provides an interfaceto up to four bump sensors. Finally, the board provides an analoginterface to monitor the battery levels of the four power circuits. Themotor driver board supports a Wheatstone Bridge daughter board tointerface to the antennal strain gauges. In addition to the connectionto the serial bus, the board has three connectors for the motors, twoconnectors for the antennae and a connector for the bump circuits andbattery monitors.

The motor driver board receives vectored serial commands from thecontroller 22 to move the antennae motor 62 to one of four positions andthe claws and tail motors 54, 56 to one of three positions. In addition,the motor board can receive a calibration command to move the motors toa mechanical stop to zero the motor position and another command toreset the motors to their “rest” position.

The motor driver board can be polled to report data from the antennae60A, 60B, the bump sensors, or the battery monitors. The antennae signalis discreetized into three degrees of bending to the left or right aswell as a rest position. The antennal interface also monitors theantennal signal to look for rapid (e.g. <150 msec) deflections to theleft or right which are characteristic of the buckling that occurs inthe antennae in response to head on collisions.

The interface boards communicate with the central processor 22 or alaptop through the serial bus. This can be achieved through reading andwriting to shift registers or in one embodiment by reading and writingbyte codes to a small PIC microcontroller and distributing or collectingthe signals over the logic pins of the processor. This allows the userto substitute a laptop for the embedded controller for debugging. Sinceall peripheral events are on/off (i.e. labeled line sensors are one bitand different bits gate on current drivers at different pulse width dutycycles), single bytes can contain both board address and data. There are256 possible sent commands and 256 possible received sensor responses.The sent commands include the ability to turn a nitinol actuator on oroff at one of three pulse width duty cycles, the ability to move theclaws 50, tail 58, or antennae 60A, 60B to different positions, theability to request sensor data or sonar commands in one of sevenformats, the ability to set or clear an external LED 18, and the abilityto set the pulse-width duty cycle LUTs to different duty cycles.Received data include one and two byte frames from the compass 24,inclinometers 26, 28, antennae, and contact sensors, as well as acousticcommands from the sonar sensor 64. The bit masks associated with thesereturned bytes are described below.

b. Lamprey-Based Undulatory Vehicle

With respect to FIGS. 5 through 9, the lamprey-based undulatory robot100 is suited for operations in, among others, the water column of theocean or relatively still bodies of water. In one illustrativeembodiment, it consists of a watertight hull 102 that is 12″ (0.3 cm)long and 4″ (0.1 cm) in diameter and a 24″ (0.6 cm) long undulatoryactuator system 104.

The illustrative vehicle weighs about three pounds (1.36 kg) in air butless than 100 grams in water when properly ballasted. Swimming thrust isgenerated by lateral axial undulations that propagate from rostral tocaudal segments. With reference to FIGS. 7A, 7B, and 8, theseundulations are generated in the illustrated embodiment by fiveundulatory modules 124 each comprising pairs of TEFLON (E.I. du Pont deNemours and Company Corporation)-insulated SMA wire (0.006″/0.15 mmdia.) muscle modules 110 that are activated in a pattern that features a20% phase lag from anterior to posterior segments and a 50% phase lagbetween the two sides. Each undulatory module includes two end and onecentral ribs 120, which in one embodiment are formed as paired TEFLONsemicircles disposed one either side of a continuous strip ofpolyurethane which forms the spine 108 of the undulatory actuator system104. KEVLAR (E.I. du Pont de Nemours and Company Corporation) strands126 and springs 130 may be used to limit the length of travel of eachmuscle module. In an illustrative embodiment, the polyurethane spine is0.125″ (3.175 mm) thick and 1.25″ (31.75 mm) high.

The hull is coupled to the actuator system 104 by a coupling 106 thatallows the pitch of the hull 102 to be altered relative to the actuatorsystem 104. FIGS. 7C, 7D and 8 illustrate a pitch/undulation module 122which is in mechanical contact with the coupling 106. Muscle modules112A, 112B are selectively contracted to realize pitch variation. Pitchalterations develop a low pressure area above or below the hull to allowthe vehicle to dive and climb.

The undulatory vehicle 100 shares much of the electronics with theambulatory vehicle 10 described above. For example, the actuator controlboard that actuates each pair of legs in the ambulatory vehicle drivesthe entire set of nitinol actuators for the undulatory vehicle.Similarly, the pitch and roll inclinometers 126, 128 and the compass 124in the mother board of the undulatory vehicle is essentially the same asthose used in the motherboard for the ambulatory vehicle, as can thesonar communications board 130 and the controller board 132. A sonartransponder 134 is in communication with the sonar communications boardthrough a watertight connection.

Typical values for the operational environment of the disclosedundulatory robot 100 embodiment include the following:

Littoral zone depth range: 0 to 50 feet;

Operational temperature: 15 to 25 degrees C.;

Operational current speeds (max.): 10 to 15 cm/sec;

Mission length (approx.): approx. ⅕ hours; and

Forward speed (max.): 15 cm/sec.

The anterior hull 102 can mount a variety of sensor packages withcapabilities for active pitch and yaw control subject to orientation ofthe vehicle.

Basic maneuverability in the illustrative undulatory robot 100 isprovided by executing the following:

Cold start and climb from bottom;

Swimming on an arbitrary heading at one of three speeds;

Turning contraction amplitude modulation on the two sides;

Climbing and diving; and

Maintaining orientation in pitch and roll planes.

(2) Neural Circuit-Based Controller

In the following, a neural circuit-based controller adapted for use inthe lobster-based ambulatory robot 10 is described. A similar controlleris adapted for use in the lamprey-based undulatory robot 100, thoughsuch is not described in detail in the following.

With reference to FIG. 11, the neural circuit-based controller 22 of theambulatory vehicle is based on the neuronal networks that mediatelocomotion, sensing, and navigation in the model organism, the lobster.These networks have been abstracted to functional objects and integratedin a distributed controller that features separate state machines foreach walking leg 12, the anterior and posterior hydrodynamic controlsurfaces 50, 52, 58, and the antennae 60A, 60B. The operational state ofthe appendages is specified by a set of eleven internal state variablesthat configure the appendage state machines on the fly.

In parallel with the optimization of the nitinol artificial muscleactuators, development and optimization of the behavioral-basedcontroller mediates stable adaptive locomotion and reactive navigation.The controller divides the step cycle of the electrically activatedartificial muscle into nine epochs: heating (which results incontraction); contraction maintenance; and cooling for each of the stepphases of early swing, late swing and stance. This is integrated withthe stack-based command sequencer.

The basic structure of the controller is a real-time loop, illustratedin FIG. 13, that polls sensors 200, manages the command stack 202,selects behavioral acts 204, and updates the leg state machines 206. Anattention module polls each of the sensors at a different rate dependingon behavioral context.

The attention module keeps a list of the clock times at which subsequentsensor polls are to occur in temporal order and updates this list everytime a sensor is read. When a sensor is polled, the result is comparedto a list of byte masks defining particular releasers. For example, ifan antennal poll detected that the left antennae is bending medially andthe right antennae is bending laterally this would constitute thepredefined releaser for a rheotaxic rotational turn to the left.

When the attention module identifies a behavioral releaser, a look-uptable is used to identify a behavioral state table associated with thatparticular releaser. The behavioral state tables are stored as resourcesin the external development program or preferably as separate files inthe embedded microcontroller.

Whenever a releaser is identified, the sequencer sets up the sequence ofcommand state changes that mediate the evoked behavior. The sequenceractually performs two tasks. First, the releaser may be used by themicrocontroller to identify a suppressor or table of incompatible actioncomponents. For example, if the evoked behavior involves forwardwalking, any instances of backward walking command components must becleared from the command stack. This suppressor action is the locus ofimplementation of behavioral choice between incompatible commands.Second, the releaser sets up the appropriate behavior by pushing thebehavioral state table on the command stack in temporal order.

Animals can evoke behavioral acts at different levels of intensity. Thisis typically mediated by neuromodulators. The behavioral sequencerallows the command state transitions to be pushed on the stack atdifferent temporal compressions in order to vary intensity. In addition,the pulse width duty cycles associated with the low, medium and highlevels of recruitment of the nitinol actuators can be varied (see FIG.10). Thus, at high intensity, the sequence of command state changes arecompressed on the stack and the recruitment state pulse width duty cyclemapped to a high level of intensity. In contrast, at low intensity thesequence of command state changes are expanded on the stack and therecruitment state pulse width duty cycle mapped to a low level ofintensity.

Many behavioral sequences are complex and involve both fixed durationepochs as well as variable duration epochs that require sensor feedbackto terminate. Such complex sequences are preferably implemented usinglinked lists, as shown in FIGS. 12 and 24. Goal achieving subsequencesmaintain ongoing states until a defined result is achieved (e.g.,turning to a particular compass heading). Achievement of the goaltriggers the next subsequence in the list.

a. Leg State Machines

A finite state machine that operates each leg controls the actuatorsassociated with different muscles. As illustrated in FIG. 14, the statemachine generates a four-element pattern that includes the elevators,protractors, depressors and retractors for forward walking and extensorsand flexors during lateral walking.

There are three levels in the organization of this exemplary statemachine. With respect to FIG. 14, the top level is the neuronaloscillator or clock of the step cycle. The oscillator divides the stepcycle into the four basic elements (top). The step cycle is divided intoa swing phase and a stance phase that alternate. The shape of theoscillator pattern defines the duration of the four elements. Thesynergies that control the coxo-basal (CB) joint occupy the early swing(elevation and depression) and the antigravity (depression) phase of thecycle. The propulsive force muscles are active in either the swing phaseor stance phase depending on the direction of walking. For each muscle,activation is divided into three epochs: (1) an early heating phasewhere the muscle is recruited at high duty cycle to initiatecontraction; (2) an intermediate phase when the muscle is recruited atthe level specified by the desired depression or speed of walking; and(3) a cooling phase where the conversion from austenite to martensite isinitiated.

During operation, the real-time kernel checks each leg during each cycleof the real-time loop to determine whether a state change is scheduledand if so passes a message to the next level of the central patterngenerator (CPG). Whenever the oscillator schedules a new step it checksthe phase of adjacent legs (contralateral and anterior or posteriordepending on the direction of walking) and if the phase of such legs isbeyond 15% of their expected phase (0.4 for adjacent legs, 0.5 forcontralateral legs) the phase of the governed legs is reset. Thisfunction mediates the inter-leg coordinating function and maintains thewalking gait.

The pattern generator coordinates the pattern of individual leg jointmovements that determines the direction of walking. Whenever a legchanges state, an LUT specifies the particular pattern of actuatoron/off transitions appropriate to the direction of walking. Thesetransitions are contingent on several internal state variables such asthe overall intensity of the behavior, the walking speed, and thedesired height, pitch and roll of the vehicle.

b. Electro-Mechanical Tuning

Extensive analysis is performed to match the leg control parameters inthe software with the mechanical responses of the leg system. This isestablished by motion analysis of the legs while going through theparameter space. The basic parameters being altered are the timing ofcontractions during different phases of the step cycle (e.g., earlyswing, late swing, and stance) and the duty cycle of the control signal.The movement of the leg tip is measured as a response to alteringparameters. The process is repeated until no further improvement isrealized.

In FIG. 15, the movement of a leg tip on the X-Y plane is plotted forvarious temporal proportions of early swing/late swing during the swingphase. All tracks are drawn in the same scale, and show the increasedelevation as the early swing (i.e. simultaneous elevation andprotraction) is lengthened as late swing (i.e. depression andprotraction) is shortened.

c. Adaptive Reflexes

Real lobsters modulate their on-going behavior through exteroceptivereflexes that respond to changes in the animal's orientation relative togravity, bumps, responses to antennal sweeps and angular andtranslational accelerations. The robot features a sequencingarchitecture that allows multicomponent sequences.

For example, rheotaxic behavior involves three subsequences: (1)lowering the body and spreading the claws; (2) rotating into the currentdetected by symmetrical deflection of antennae held laterally to thebody; and (3) pitching forward, pitching claws down and tail up toproduce a force vector into the substrate and proceeding forward with aload compensating gait.

The first and third elements of this sequence are fixed in duration. Themajor variable is the second element that actually involves iteration ona goal. These behavioral sequences are grouped in a list of behavioralstate tables. During modulation of a sequence, the sequencer pushes thefirst table into the list and when it completes places the second tableon the list, etc. In the case of goal achieving sequences, the sequencersets the appropriate state variables (e.g., walking forward on one sideand backward on the other to rotate into the flow) and a desired goal(e.g., a symmetric lateral deflection of the antennae), wherein the nextstate table in the list is triggered when that goal is achieved.

The behavior of the robot also includes a taxic component superimposedon the behavioral sequences. For example some sensors act directly oncommand neurons through exteroceptive reflexes.

In FIGS. 16A and 16B, exteroceptive reflexes are shown mediatingrheotaxic responses to asymmetric flow and surge. Specifically, in FIG.16A, an asymmetric flow registers as a low magnitude lateral force inthe left antenna lateral sensor and a medium magnitude lateral force inthe right antenna lateral sensor. The appropriate behavioral response isthen implemented—i.e. left side walking at medium intensity and rightside walking at low intensity. FIG. 25 illustrates a command sequencenecessary for achieving the desired behavioral response to the detectedflow. Similarly, in FIG. 16B, a surge from the right is detected as ahigh magnitude lateral force by the left antenna lateral sensor and ahigh magnitude medial force by the right antenna medial sensor. Therheotaxic interneuron for a right surge is identified, and highintensity forward movement results on the left side, while highintensity rearward movement results on the right.

d. Supervised Autonomy

The vehicle is intended to operate autonomously while supervised bysonar commands from an operator. In other words, an operator can givethe vehicle high order commands but the reactive behavior relative toenvironmental contingencies is autonomous. FIG. 23 illustrates a wake-upsequence performed by the controller. FIG. 26 illustrates a commandsequence executed by the controller to enable responsiveness to externalcommands.

As illustrated in FIG. 17, the autonomous capabilities are maintained byan event loop 220 that nests both behavioral sequences and exteroceptivereflexes. The actual movements of the vehicle are generated by a set ofstate machines that control the legs, claws, tail and antennae. Theseactuators generate movement and collisions that are sensed by the sensorpolling interface. Returned sensor data are subjected to bit maskfilters that detect behaviorally significant releasers. The releaserspush evoked behavioral sequences onto an event or command stack. Thestack pops events that modulate the state variables of the statemachines. As shown, certain sensor inputs represent exteroceptivereflexes, which are used to modulate the state machine variables withoutdirectly altering the command stack contents.

During operation the vehicle can be deployed on search vectors. Assuggested by FIG. 18, a compass heading and a period of time to locomoteon that heading will specify each search vector. During execution of thesearch vector, the vehicle will be given a propensity to investigate ornegotiate objects which it encounters. This propensity will be a scalarfrom 0.0 to 1.0. In the case of an ambulatory lobster-based robot usedfor mine detection, the propensity to investigate will be determined bythe proximity to suspected mine candidates at the initiation of thevector.

(3) Myomorphic Actuators

The effectors (i.e. legs and/or body axis), control surfaces andadaptive sensors are actuated by myomorphic actuators composed ofartificial muscle, which in an exemplary embodiment is nitinol.Sequential recruitment of control synergies produce graded forces by thesize principle of neuromuscular recruitment. This recruitment isimplemented with shape memory alloy (SMA)-based actuators, but it couldbe realized by a variety of actuator technologies.

In the case of nitinol, wire treatment is necessary to remove an oxidecoating that results from the annealing process. In addition, there is atendency for seawater to infiltrate the TEFLON sleeves over extendedperiods of operation. Paired groups of identical SMA actuators areassembled and trained, one being maintained as a control and the othertreated, such as with acid or abrasive. Comparison of the followingparameters indicate that acid bath treatment improves the overallperformance of the SMA: rise time (time zero to full contraction),linear strain, resistance (pre- and post-training), and average power.Significant discrepancies in rise time were found between sand and acidtreatment, and wet and dry modules.

To address the issues of variable actuator performance due to waterinundation and frequent failure of the KEVLAR (E.I. du Pont de Nemoursand Company Corporation) attachment points, a nitinol crimp assembly isused. Initial testing has shown the design to be durable with no wateringress. As shown in FIGS. 10 and 19, the design uses a single crimp ofmaterial such as stainless steel (S.S.), onto which an electricalconductor is soldered. The nitinol wire is passed through the stainlesssteel crimp, and doubled back into the crimp to form a loop. Aftercrimping, the KEVLAR strand is attached to the nitinol by a simplehitch. This design eliminates the need to crimp the KEVLAR leads to thenitinol, a situation that has caused most observed muscle modulefailures. The observed failures involved both slippage of KEVLAR and thesevering of the KEVLAR inside the crimp, both due to the relativesoftness of the KEVLAR strand.

Water ingress into the module has been eliminated by using an etchedTEFLON tube, to which a number of sealing compounds adhere well. Thetube is supplied by Zeus Industrial Inc. (Orangeburg, S.C.), whoseproprietary etching technology creates a porous surface to the TEFLONwhile also altering the chemistry of the outer surface of the TEFLON tobecome chemically more reactive and receptive to bonding. The final stepin the module assembly process is to coat the exposed crimp assemblywith a urethane coating and to slip a length of 8 mm PVC heat-shrinktubing over the entire assembly.

An integral part of the module assembly system is the use of a pneumaticcrimping system. A die produces consistent results and gives thenecessary breakage strength to the crimp.

(4) Neuromorphic Sensors

The sensors used in the robots produce a labeled-line code based onsensor modality and receptive field and range magnitude fractionation ofthe modality, such that different labeled-lines code input of differentamplitudes. These sensors use both Micro-Electro-Mechanical Systems(MEMS)-based technology and combinations of analog sensors with amicrocontroller that quantizes the input.

In order to realize functional antennal sensors, strain gauges (notillustrated) are used to monitor bending. The strain gauge is mounted inthe middle of the antennae and interfaced to the motor-driver boardusing a Wheatstone Bridge circuit. A PIC microcontroller digitizes theanalog signal and discreetizes it to an eight bit labeled line code.Each of the bits represents one of the eight states depicted in FIG. 20.

A pair of anterior-mounted 10″ flexible polyacrylate tactile antennaeare used on the illustrated lobster system. These antennae can beprojected at four different angles depending on context. They arecapable of distinguishing water currents from collisions with solidobjects such as rocks. The byte masks associated with the two antennaemust be interpreted in the context of the position of the antennaerelative to the hull. For example, the buckling bit can be set by ahead-on collision if the antennae are projected forward or by acollision to either side if they are projected laterally. Thus,identification of releasers requires that the returned data areinterpreted through a decision tree based on the position or movement ofthe antennae. Responses must also be interpreted in the context ofmovements between positions that can bend the antennae.

As noted with respect to FIG. 1, the antennae 60A, 60B are controlled bya motor drive 62 which allows them to sweep over arbitrary rangesbetween four basic positions. If the antennae collide with an object ina sweep range it will indicate bending by the magnitude of sensorflexion. One of the additional characteristics of the underwateroperation of these sensors is that they buckle when they make a head-oncollision with an object. This is associated with a rapid left-rightbend of the antennae. The PIC microcontroller is programmed to recognizesuch events and sets the eighth bit for each antennae for 150 msecfollowing such collisions.

The antennae 60A, 60B have been calibrated in a laminar flow system suchthat they can also be used to indicate water flow, both in terms ofdirection and magnitude. For example, if the antennae are staticallyprojected forward and both are bent to the right this would indicateflow from the left. If the antennae are projected statically laterally,they become a flow sensor for anterior originating currents and canindicate when the vehicle is oriented into flow or surge on the basis ofsymmetric deflections on both sides.

Pitch and roll inclinometers 26, 28, each having an eight bit labeledline code for each of pitch and roll over a +/−80° range relative tohorizontal, are used in the illustrated system. A flux gate compass 24has an interface that provides three bits of resolution (i.e. eightheading sectors—N, NW, W, SW, S, SE, E, NE).

(5) Reactive Autonomous Behavior and Behavioral Libraries

The basic premise of biomimetics is that the vehicle can achieve theperformance advantages that the animal model enjoys in the naturalenvironment by mimicking the behavior of the model. The approach toachieving the behavioral repertoire of the lobster is to base thevehicle control architecture on the prevailing neuronal network model ofthe motor systems, the command neuron, and the coordinating neuroncentral pattern generator architecture.

The fundamental assumption of this behavioral control model is that theposture and action of the different body parts is specified by a set ofcommand systems that command the task group to generate a differentstate. Thus, the task of deriving the underlying behavioral scripts isto specify the state of the task groups in each of the frames of a movieof the model animal performing the act that one wants the vehicle tomediate. The following set of states are adequate to define the ongoingbehavior of both the lobster and the biomimetic robotic vehicle.

Thorax Pitch: rostrum up, level, rostrum down

Thorax Roll: left up, level, right up

Thorax Yaw: hard left, easy left, straight, easy right, hard right

Thorax Height: high, normal, low

Walking direction: standing, forward, backward, lateral leading, lateraltrailing

Walking speed: slow, medium, fast, stop

Claw Pitch: up, normal, down

Claw Yaw: extended, normal, meral spread, lateral spread

Antennae Yaw: protracted, normal, lateral, retracted

Uropod Posture: flared, normal, adducted

Abdominal Pitch: extended, elevated, normal, depressed, flexed

To derive robotic control sequences from video data of the subjectanimal, finite state analysis of task groups that mediate locomotion isperformed using a software tool such as ColorImage, developed by theMarine Science Center of Northeastern University, East Nahant, Mass. Anexemplary display of such a program is shown in FIG. 21. The videoframes 250 are searched individually to abstract command states and todetermine which synergistic sets are operant during different behavioralacts. This analysis of the sequencing of task groups borrows from atechnique utilized by astronomers to detect motion of objects such ascomets. As the analysis proceeds through each frame of the digitalmovie, the program flashes between temporally adjacent frames with abrief pause after each cycle. Appendages that are moving the most flashin these projections. A panel of buttons 252 that represent differentstates of the task groups (e.g., elevation versus depression of thechelipeds, etc.) are available to the investigator to specify whichgroups are active. By clicking on the appropriate buttons for eachframe, it is possible to efficiently quantify the activity of all taskgroups at high temporal resolution from video recordings of specimensbehaving in a variety of situations. A display 254 of the vehicle withthe selected state active may be displayed for reference purposes. Thesestate change sequences constitute the behavioral library of thevehicles.

A behavioral editor that allows one to refine the behavioral statetables 256, shown in FIG. 22, is also used to generate standardbehavioral sequences that are then stored in the memory of the vehicle.Each behavioral sequence is associated with a unique releaser thattriggers it in response to the right environmental contingencies.

Alternative embodiments to the presently disclosed robots include theincorporation of a low-power acoustic modem and embedded signalprocessing platform, such as the Woods Hole Oceanographic Institution(WHOI) Micro-Modem, into the vehicle to allow integrated control andnavigation. A supervisory acoustic communications-based operatorinterface can also be provided that will allow waypoint navigation andsupervision of ongoing search and investigation. This navigationimprovement is used to train the systems to achieve the capability tomediate coordinated autonomous search in regions of bottom clutter andconduct homing operations on a sonar beacon.

By developing a set of investigatory and reporting behaviors,identification of and response to sensed objects can be achieved. Thisfunctionality may require the incorporation of additional sensors,depending upon the mission requirements. For example, optical flow chipssuch as those produced by CentEye (Washington, D.C.) to instantiateoptomotor reflexes in the robots.

As an alternative to the nitinol SMA actuators, the Honeywell PolyMEMSActuator, a polymer-based MEMS microactuator with macroscopic action,may be utilized to implement muscle in adapting robot systems to land.Further, the neuronal networks that underlie the presently disclosedfinite state machine controller could be implemented with theHindmarsh-Rose electronic neurons of the University of California at SanDiego Institute for Non-Linear Science.

Commercial applications for the presently disclosed biomimetic robotsincludes remote sensing and mine countermeasures in the littoral zone ofthe ocean and/or rivers and streams. The vehicles may be delivered intorpedo cache systems or from small craft to an area to be investigatedand cleared. The overall scenario is for the robots to achieve acomprehensive search of a mine candidate area using a swarm ofautonomous vehicles. The set of behavioral acts that a lobster employsto search for food is exactly what a mine hunting robot needs to performto localize and identify mine candidates. Thus, the behavioral set ofthese vehicles is beneficially derived directly from reverse engineeringof the behavioral sequences of real lobsters. Additional embodiments ofthese robots rely on electro-optical imaging as well as near-fieldqueues, which are primarily tactile, and chemical detectors in thelocalization of mine candidates. By using swarms of the vehicles, theprobability of collision with mine candidates is maximized.

The vehicles performing such tasks operate as supervised autonomousagents in a landing lane delineated by a stand-off lane marking systembased on sonobuoys and acoustic modems, or alternatively on the basis ofsatellite positioning systems such as GPS in the case of tetheredvehicles towing floats. The role of the lane marking system is two-fold:(1) to constrain the search within the candidate landing zone; and (2)to supervise the search activities to insure complete coverage. A mastercontroller supervises the movement of the vehicles and maintains arecord of the tracks of the vehicles. The controller uses this record toconstrain the movements of the vehicles to insure a complete searchpattern, though the search will be random at the level of the individualvehicles. As the operation proceeds, the supervisory system willinfluence the vehicles to insure complete coverage of the landing lane.

Ambulatory vehicles can be used for searching the bottom whileundulatory vehicles can be used for searching the water column. Thelanding lane will be delineated by a set of four sonobuoys that areequipped with high frequency transponders. During initiation of asearch, the vehicles will initiate a search segment on an arbitraryheading, and then annunciate a current position, allowing the mastercontroller to use the acoustic cues to localize the position of thevehicle. When the position is determined, the vehicles will be given aheading and an arbitrary length of time to walk on that heading. At theend of that time period, the vehicle will announce completion of thatsegment of the search (see FIG. 18). This search segment procedure willrepeat to allow comprehensive coverage. As the search proceeds therecord of search paths will be used to determine regions of low searchcoverage and the controller will direct additional search segments inthose areas in a probabilistic fashion.

Such an algorithm assumes that the behavior of the robot is autonomousduring a search segment and that the competencies of the vehicle allowit to deal with environmental contingencies. Such obstacles mightinclude uneven substrates, rocks, boulder fields, shoals, wave surge,tidal currents, algal beds, etc. The vehicle will have the overlyingmotivation to navigate on a specified compass heading. When itencounters an obstacle, the robot will attempt to ascertain whether itis a mine candidate or not.

There are numerous types of sensors that can be used for mineidentification currently under development including electronic noses,acoustic hardness testers and active electric field perturbationsensors. The investigative behaviors adopted from lobsters will insurethat the sensors can be both brought into adequate proximity and bedeployed from all orientations relative to the mine candidate. If thevehicle determines that the obstacle is not a mine candidate it mustmake the decision whether to climb over the obstacle or to transversearound it. The vehicles will use a combination of antennal sensors andclaw like surfaces to ascertain whether climbing is feasible. Whereclimbing is unfeasible the vehicle will use a wall following algorithmto locomote around the obstacle until it can resume its predeterminedheading.

This basic scenario will apply to almost all sea floor types. Where thesubstrate slopes the vehicle will rely on orientational reflexes tomaintain stability in the pitch and roll planes. The vehicles are ableto streamline their claw like control surfaces to allow them to plowthrough algal beds. Operation in the littoral zone or in rivers willrequire adaptations to current and wave surge.

The illustrated vehicle embodiment is statically stable in currents upto one knot. When wave surge exceeds these rates and especially when therate of change of current is high, the vehicles will evoke a sequence ofrheotaxic behavioral acts that will serve both to streamline the vehicleas well as insure hydrodynamic stability. These rheotaxic acts willinclude yawing into the current, pitching the body forward, lowering theclaw-like control surfaces and elevating the tail-like control surfaces.Each of these components of rheotaxic behavior will have a definedthreshold as perceived by current and shear sensors. Due to a largedifference between the center of gravity and center of mass due to thelow placement of the batteries, the vehicle is statically stable andself-righting in case of major perturbations.

During investigation the vehicle relies on capabilities foromni-directional locomotion to circle around an object while maintainingsensor suites on the object at close proximity. By performing thisprocedure, the vehicle can use voting algorithms from differentorientations to fuse information about the size, shape, surfaceproperties, and electrical, magnetic or chemical signatures that it mayuse for identification. Incorporation of the WHOI Micro-Modem referencedabove allows the vehicle to telemeter images of a mine candidate forpositive electro-optical identification. At the completion of themission, the vehicles can be commanded to deploy a miniature lift bag toforce them to float to the surface where they can be collected forreuse.

The undulatory robot is intended to complement the operation of theambulatory robots in performing search operations for mine candidatesthat are suspended in the water column. It will similarly be deliveredto the operational theatre by torpedo cache systems or small craft andwill be governed in its search behavior by the same lane marking systemas the ambulatory vehicle. During searches, the vehicle will navigate onsearch segments which are specified by a compass heading.

The vehicle can use a sonar altimeter to regulate its altitude to thatof suspended tethered mine candidates. While swimming on an arbitraryheading, the vehicle will use high frequency directional sonar toinsonify the water in front of the vehicle and listen for sonar returnsthat indicate a close range object. Since the vehicle will be undulatingin the yaw plane, the sonar will be scanning laterally. If the vehicleretains the compass heading at which it generated the sound pulse, itcan use omni-directional sonar receivers to correlate the reception ofan echo at short latency with the orientation of the transmitter whenthe pulse was generated. By this mechanism the vehicle will be able tolocalize the orientation of candidates relative to the vehicle.

While the present invention has been described in conjunction with apreferred embodiment, one of ordinary skill, after reading the foregoingspecification, will be able to effect various changes, substitutions orequivalents, and other alterations to the compositions and methods setforth herein. It is therefore intended that the protection granted byLetters Patent hereon be limited only by the definitions contained inthe appended claims and equivalents thereof.

1. A method of realizing biomimetic behavior in a robot, comprising:identifying plural physical components of a subject animal, each capableof being physically displaced with respect to each other; identifying aphysical maneuver performed by at least one of the physical componentsof the subject animal; for each of the at least one physical componentsperforming the identified physical maneuver, identifying changes inphysical orientation over time; forming a behavioral sequence filecomprised of the changes in physical orientation for each of the atleast one physical components required to perform the identifiedphysical maneuver over the time required to perform the identifiedphysical maneuver; providing a robot comprising a body with an interiorbody cavity and an exterior body surface having a counterpart componentfor each of the identified plural physical components of the subjectanimal, each of the counterpart components being independentlyactuatable; providing a controller in association with the robot, thecontroller including a memory and being capable of issuing commands toactuate each of the counterpart components; forming a behavioral libraryin the controller memory, the behavioral library comprising, for arespective physical maneuver, a command sequence, each command of thecommand sequence for actuating a counterpart component to achieve achange in physical orientation therein, the command sequence causingchanges in physical orientation for each of the at least one counterpartcomponents required to perform the identified physical maneuver over thetime required to perform the identified physical maneuver in accordancethe behavioral sequence file; and commanding the robot to perform theidentified physical maneuver through the controller issuing therespective command sequence from the behavioral library to achieve thechanges in physical orientation for each of the at least one counterpartcomponents required to perform the identified physical maneuver over thetime required to perform the identified physical maneuver.
 2. The methodof claim 1, further comprising the steps of: identifying plural physicalmaneuvers to be performed by the robot; forming a behavioral commandsequence data file in the controller memory comprised of a commandsequence for each of the identified plural physical maneuvers; andcommanding the robot to perform the identified plural physical maneuversthrough the controller issuing the respective command sequences from thebehavioral library to achieve the changes in physical orientation foreach of the at least one counterpart components required to perform theidentified plural physical maneuvers.
 3. The method of claim 2, furthercomprising the steps of: providing at least one sensor in associationwith the robot, the sensor providing an output in communication with thecontroller; and selectively altering the step |_([GRM1])of commanding inresponse to the sensor output.
 4. The method of claim 3, furthercomprising: identifying step cycles for each of the plural physicalmaneuvers; providing a neuronal oscillator circuit for dividing the stepcycles into elemental phases; identifying a parameter space throughwhich the at least one physical component moves; analyzing the motion ofthe counterpart component through the parameter space and matching atleast one parameter for controlling the counterpart component withmechanical responses of the counterpart component; identifying from thebehavioral command sequence data file an expected phase for the at leastone counterpart component performing the identified maneuver for eachphase of the step cycle; checking the phase of the at least onecounterpart component with the oscillator circuit during a step cycle ofthe identified maneuver; comparing the checked phase of the at least onecounterpart component with its expected phase according to thebehavioral command sequence data file; and providing the result of thecomparison to the controller.
 5. The method of claim 4, furthercomprising the step of selectively altering the step cycle of at leastone of the plural physical maneuvers by at least one of phase advancesand delays in response to the sensor output.
 6. The method of claim 3,further comprising: wherein the at least one sensor is for sensing atleast one of the ambient temperature, collision with an object externalto the robot, and velocity relative to one or more geographiccoordinates or the external chemical medium surrounding the exteriorsurface of the robot.
 7. The method of claim 3, wherein the at least onesensor is selected from the group consisting of at least one antennahaving strain gauges operatively associated therewith and at least onebump sensor.
 8. The method of claim 7, further comprising: electricallycoupling the strain gauges of the at least one antenna or the at leastone bump sensor to the controller; and detecting a collision between theantenna and an external object using the output of the strain gauges, orbetween the bump sensor and an external object using the output of thebump sensor, and providing an indication thereof to the controller. 9.The method of claim 3, wherein the step of providing at least one sensorfurther comprises: providing the robot with at least one optical flowchip and electro-optical image processing capability in the controllerto realize autonomous optomotor reflexes.
 10. The method of claim 2,further comprising: providing a plurality of sensors; providing sensorfusion signals, wherein combined signals from at least two of theplurality of sensors are communicated to the controller; developing aset of investigatory and reporting behaviors as part of the behavioralcommand sequence data file, wherein said investigatory and reportingbehaviors are selectively modulated in response to the sensor fusionsignals whereby objects or conditions external to the robot may besensed; commanding the robot to investigate and report on objects orconditions external to the robot according to the set of investigatoryand reporting behaviors; and identifying and responding to sensedobjects or sensed conditions.
 11. The method of claim 2, furthercomprising: forming conflicting state files in the controller memory,the conflicting state files defining how conflicting controller commandsare to be resolved when commanding the robot to perform pluralidentified physical maneuvers, prior to actuation of the counterpartcomponents required to perform the identified plural physical maneuvers;and commanding the robot to perform the identified plural physicalmaneuvers through the controller issuing the respective commandsequences from the behavioral library with reference to the conflictingstate files implicated by the performance of the respective, identifiedplural physical maneuvers.
 12. The method of claim 1, furthercomprising: identifying at least one physical maneuver or sequence ofmaneuvers, or modification to an on-going physical maneuver, thatcomprises an exteroceptive reflex of the subject animal in response toat least one condition or parameter external to the subject animal;modifying the behavioral sequence file to include a response componentassociated with the exteroceptive reflex, the response componentcomprising the changes in physical orientation for each of the at leastone physical components performing the identified at least one physicalmaneuver or sequence of maneuvers, or modification to an on-goingphysical maneuver, over the time required to perform the exteroceptivereflex; providing at least one sensor in association with the robot forsensing the at least one external condition or parameter and forproviding the controller with an indication thereof; modifying thebehavioral library, for a respective at least one external condition orparameter as sensed by the at least one sensor, to include a reflexcommand sequence, each command of the reflex command sequence foractuating a counterpart component to achieve a change in physicalorientation therein, the reflex command sequence causing changes inphysical orientation for each of the at least one counterpart componentsrequired to perform the identified at least one physical maneuver orsequence of maneuvers, or modification to an on-going physical maneuver,over the time required to perform the identified at least one maneuveror sequence of maneuvers, or modification to an on-going physicalmaneuver, that comprises the exteroceptive reflex in accordance with thebehavioral sequence file; and commanding the robot to performautonomously in response to the at least one sensor sensing the at leastone external condition or parameter through the controller issuing therespective reflex command sequence from the behavioral library toachieve the changes in physical orientation for each of the at least onecounterpart components required to perform the identified at least onephysical maneuver or sequence of maneuvers, or modification to anon-going physical maneuver, associated with the exteroceptive reflex.13. The method of claim 12, wherein the exteroceptive reflex is arheotaxic or orientational response.
 14. The method of claim 1, furthercomprising: providing the robot with a battery compartment and aplurality of batteries therein; and dividing the plurality of batteriesinto parallel sets of power circuits, each set of power circuitscomprising plural ones of the plurality of batteries, the plural onesbeing connected in series.
 15. The method of claim 1, furthercomprising: providing the controller with an acoustic modem receiver;and supervising the robot from a remote location via an acoustic modemtransmitter.
 16. The method of claim 1, further comprising: programmingthe controller to move the robot with a propensity to investigate atarget object, wherein the propensity to investigate is dependent uponthe proximity to the target object.
 17. The method of claim 1, furthercomprising: providing the robot with a sonar transceiver incommunication with the controller; and modulating the step of commandingbased upon data from the sonar transceiver.
 18. The method of claim 1,wherein the step of providing a controller comprises providing acontroller composed of synaptically connected electronic neuronsconfigured as a neural network.
 19. The method of claim 1, wherein thestep of commanding the robot further comprises: issuing the respectivecommand sequence including the steps of turning actuators associatedwith the at least one counterpart components on or off according to arespective pulse-width duty cycle.
 20. The method of claim 19, whereinthe step of commanding the robot further comprises: providing the robotwith an environmental sensor in communication with the controller, theenvironmental sensor for providing an environmental characteristic; andmodulating the respective pulse-width duty cycle according to the sensedenvironmental characteristic.
 21. The method of claim 1, furthercomprising: providing the controller with a serial bus interface forselectively communicating with a peripheral interface controller. 22.The method of claim 1, further comprising: providing program code to thecontroller via a removable memory module or a PCMCIA adapter associatedtherewith.
 23. The method of claim 1, further comprising: incorporatinginto the robot a low-power acoustic modem and imbedded signal-processingplatform to allow integrated control and navigation.
 24. A method ofcontrolling a biomimetic robotic system for autonomous operation, therobotic system having a biomorphic physical plant that is based on aninvertebrate animal model having a neuronal network, the physical plantincluding a plurality of sensing devices including sensing antennae,anterior and posterior hydrodynamic control surfaces, a memory, aplurality of motoring mechanisms, a state machine for each of theplurality of motoring mechanisms, a behavioral sequencer for ordering aplurality of behavioral responses in a desired temporal order, and aneural circuit-based, behavior-based controller that is modeled afterthe neuronal network of the animal model, for mediating stablelocomotion, reactive navigation, and sensing of the robotic system andthe environment surrounding it, the method comprising: polling data fromthe plurality of sensing devices; comparing the polled data withpredefined releasers, stored in behavioral libraries stored in thememory, to identify a unique behavioral releaser corresponding to saidpolled data; preparing to execute a sequence of command state changesfor at least one of the state machines, to mediate an evoked behaviorcorresponding to the unique behavioral releaser; placing the sequence ofcommand state changes into a temporal location within a command stack ofexecutable sequences, to cause said sequence of command state changes tobe executed upon reaching the temporal-based location in said commandstack; and executing the sequence of command state changes sequentiallyin accordance with the temporal-based order of the command stack. 25.The method as recited in claim 24, wherein polling data from theplurality of sensing devices includes producing labeled-line code basedon sensing device modality.
 26. The method as recited in claim 24,wherein preparing to execute the sequence of command state changesincludes identifying and suppressing or modifying any conflicting statechanges already present in the command stack.
 27. The method as recitedin claim 24, wherein placing the sequence of command state changesincludes varying an intensity of a respective command state change byusing different temporal compressions therefor.
 28. The method asrecited in claim 27, wherein using different temporal compressionsincludes using pulse width modulation of a respective duty cycle. 29.The method as recited in claim 24, wherein each of the plurality ofmotoring mechanisms includes at least one elevator, at least oneprotractor, at least one depressor, and at least one retractor, eachbeing selectively actuatable to enable forward and rearward movement,and at least one extensor and at least one flexor, each beingselectively actuatable to enable lateral movement, the method furthercomprising controlling at least one of the state machines to actuate acorresponding one of said at least one elevator, said at least oneprotractor, said at least one depressor, said at least one retractor,said at least one extensor or said at least one flexor.
 30. The methodas recited in claim 24, further comprising: checking a phase of adjacentones of said plurality of motoring mechanisms prior to execution of asequence of command state changes on a respective motoring mechanism;and resetting the phase of said respective motoring mechanism if thephase of any of the adjacent motoring mechanisms would conflict with theexecution of the sequence of command state changes on the respectivemotoring mechanism.
 31. The method as recited in claim 24, whereinplacing the sequence of command state changes includes performingmulti-component sequencing to perform at least one of a rheotaxicbehavioral response and an exteroceptive behavioral response.
 32. Themethod as recited in claim 24, wherein the step of comparing furthercomprises comparing the polled data with predefined releasers, stored inthe behavioral libraries stored in the memory, to identify anexteroceptive reflex, and further comprising the step of modulating atleast one state machine without altering the command stack of executablesequences based upon identification of an exteroceptive reflex.